Research on node properties of resting-state brain functional networks by using node activity and ALFF

Abstract

Human brain functional networks have some attractive topological properties in anatomical space, whereas relatively few literatures to discuss the local properties of brain networks. In this paper, a method for judging nodes properties of resting-state brain functional networks is proposed based on node activity and Amplitude of Low Frequency Fluctuation (ALFF). We utilized it to research the active degree of brain regions. Firstly, functional Magnetic Resonance Imaging (fMRI) data are employed to construct the resting-state brain functional network, and calculate node degree, clustering coefficient and average distance. Then, by comparing the differences in the above indexes between stroke patients and normal subjects, we further analyzed the distribution of active degree in various brain regions and their connection states through node activity of brain functional networks. Finally, the ALFF values of normal subjects and patients are measured respectively in contrast experiment, and the activity of the related nodes was compared and judged. The node activities of some brain regions in stroke patients are lower than that of normal subjects and even zero, and the ALFF values of the normal are generally higher than those of the stroke patients. The experimental results verify the feasibility of node activity in judging active degree of various brain regions from physiological significance of ALFF in resting-state brain functional networks.